python - Create multiple dataframes in loop

Question

I have a list, with each entry being a company name

companies = ['AA', 'AAPL', 'BA', ....., 'YHOO']

I want to create a new dataframe for each entry in the list.

Something like

(pseudocode)

for c in companies:
     c = pd.DataFrame()

I have searched for a way to do this but can't find it. Any ideas?

Answer 1

Just to underline my comment to @maxymoo's answer, it's almost invariably a bad idea ("code smell") to add names dynamically to a Python namespace. There are a number of reasons, the most salient being:

1. Created names might easily conflict with variables already used by your logic.

2. Since the names are dynamically created, you typically also end up using dynamic techniques to retrieve the data.

This is why dicts were included in the language. The correct way to proceed is:

d = {}
for name in companies:
    d[name] = pd.DataFrame()

Nowadays you can write a single dict comprehension expression to do the same thing, but some people find it less readable:

d = {name: pd.DataFrame() for name in companies}

Once d is created the DataFrame for company x can be retrieved as d[x], so you can look up a specific company quite easily. To operate on all companies you would typically use a loop like:

for name, df in d.items():
    # operate on DataFrame 'df' for company 'name'

In Python 2 you are better writing

for name, df in d.iteritems():

because this avoids instantiating a list of (name, df) tuples.